Relatively large and sophisticated web sites typically implement some form of personalization system to provide personalized content, such as personalized item recommendations, to their users. Such personalization systems may, for example, monitor and record one or more types of item-related user activity such as item purchases, item viewing events, and/or item rentals, and analyze the collected data to detect and quantify associations between particular items. When a user accesses a particular item, such as a particular product in a catalog of an e-commerce site, or an article on a news site, an appropriate message may be displayed notifying the user of related items (e.g., “people who viewed this item also viewed . . . ,” or “based on your recent purchases, you may also be interested in . . . ”). The personalization system may also generate personalized item recommendations that are based on a target user's purchase history, item viewing history, item ratings, and/or some other type of user data.
Unfortunately, personalization systems can be expensive to implement and maintain. For example, a relatively sophisticated personalization system typically requires infrastructure components which, among other tasks, store customer behavior data, process the stored behavior data to detect the item associations, and store databases which relate items to one another. As a catalog of items to be recommended increases, the amount of data and computing power needed to generate the recommendations grows significantly. As a result, among other reasons, sophisticated personalization systems are implemented, in many cases, by relatively large companies that can start and maintain such systems.
Moreover, for a variety of reasons, some personalization systems tend to rely on a limited set of behavioral data from which to provide personalized content. Since the value to end-users of personalization services is dependent on the size and quality of the underlying datasets from which personalization associations are drawn, further improvements in the amount and application of behavioral data captured is desirable.